Timeline: 2019-08-29 09:35:00 - 2020-11-20 16:10:00

# g <- ggplot(data=intra) + theme_classic() +
# geom_line(aes(x=Date,y=SPX)) +
# scale_y_continuous(limits=c(0, 50)) +
# labs(x="Date", y="S&P 500 Price")
ay <- list(
tickfont = list(color = "red"),
overlaying = "y",
side = "right",
title = "S&P 500 Volatility"
)
fig <- plot_ly()
fig <- fig %>% add_lines(x = intra$Date, y = intra$SPX, name = "S&P 500 Price")
fig <- fig %>% add_lines(x = intra$Date, y = intra$e, name = "S&P 500 Volatility", yaxis = "y2",opacity = 0.5)
fig <- fig %>% add_lines(x = as_datetime("2020-03-03 10:00:00 "), y = intra$e, name = "Rate Cut 03/03", yaxis = "y2",opacity = 1.0)
fig <- fig %>% add_lines(x = as_datetime("2020-03-16 09:45:00 "), y = intra$e, name = "QE 03/15", yaxis = "y2",opacity = 1.0)
fig <- fig %>% add_lines(x = as_datetime("2020-03-23 09:30:00 "), y = intra$e, name = "QE 03/23", yaxis = "y2",opacity = 1.0)
fig <- fig %>% add_lines(x = as_datetime("2020-04-06 09:30:00 "), y = intra$e, name = "LF 04/06", yaxis = "y2",opacity = 1.0)
fig <- fig %>% add_lines(x = as_datetime("2020-04-28 09:30:00 "), y = intra$e, name = "LF 04/27", yaxis = "y2",opacity = 1.0)
fig <- fig %>% add_lines(x = as_datetime("2020-07-28 09:30:00 "), y = intra$e, name = "LF 07/28", yaxis = "y2",opacity = 1.0)
fig <- fig %>% layout(
title = "S&P 500 Index Level and Return Volatility", yaxis2 = ay,
xaxis = list(title="Date"), yaxis1 = list(title = "S&P 500 Index")
)
fig